Analysis of factorial time-course microarrays with application to a clinical study of burn injury.

ABSTRACT: Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across the time course while accounting for multiple testing and nonnormality of the microarray data. The method effectively extracts gene-specific response features and models their dependency on the experimental factors. Both longitudinal and cross-sectional time-course data can be handled by our approach. The method was used to analyze the impact of age

SUBMITTER: Zhou B 

PROVIDER: S-EPMC2890487 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature